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- W2106339924 abstract "Automatic discrimination of speech and music is an important tool in many multimedia applications. Previous work has focused on using long-term features such as differential parameters, variances and time-averages of spectral parameters. These classifiers use features estimated over windows of 0.5-5 seconds, and are relatively complex. We present our results of combining the line spectral frequencies (LSFs) and zero crossing-based features for frame-level narrowband speech/music discrimination. Our classification results for different types of music and speech show the good discriminating power of these features. Our classification algorithms operate using only a frame delay of 20 ms, making them suitable for real-time multimedia applications." @default.
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- W2106339924 date "2002-11-07" @default.
- W2106339924 modified "2023-09-27" @default.
- W2106339924 title "Speech/music discrimination for multimedia applications" @default.
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- W2106339924 doi "https://doi.org/10.1109/icassp.2000.859336" @default.
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